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Updated: Mar 7, 2026

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording
Published on: August 11, 2019
Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity
Elena Bertolotti1,2, Raffaella Burioni1,2, Matteo di Volo3,4,5
1Dipartimento di Fisica e Scienza della Terra, Università di Parma, via G.P. Usberti, 7/A-43124 Parma, Italy.
Abstract:
We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons f_{I} and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on f_{I}, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.
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